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This paper focuses on the planning of electricity resources in the developing electricity infrastructure. First we model the existing infrastructure and extend this model to a smart grid infrastructure, where we focus on the large scale introduction of small electricity generators, leading to generation possibilities at both ends of the electricity network. Then the traditional Unit Commitment Problem (UCP) is given. We extend this formulation to the Multilevel Unit Commitment Problem (MUCP), where we describe and include the possibilities that arise in the developing smart grid, in a general way. Based on the characteristics of the problem with its subdivision into different levels, a planning method for the MUCP is described. Finally we solve and analyze a scenario, where a fleet of 5000 houses is added to a small collection of power plants.

Small but numerically dominant species such as the cyanobacteria Prochlorococcus play a pivotal role in major nutrient cycles. To understand how Prochlorococcus populations affect nutrient flows, we present and analyze two alternative population models. These models − one including over-shading effects and one not − are based on Dynamic Energy Budget (DEB) theory to describe how growth may be affected by the availability of CO2 and/or inorganic nutrients and by changes in light conditions. In these models individuals have reserves for C, N, and P from which fluxes for maintenance and growth are mobilized. Time series data from laboratory studies of growth under three different nutrient concentrations are used to calibrate the models. The model with carbon, nitrogen and phosphate as limiting factors can reasonably describe the growth in the low N and low P media experiments, while the model with over-shading gives a proper description of the growth under all tested experimental conditions. Modeled C:N:P ratios are within range of reported in scientific literature ones and similar to measured ratios. The results suggest that (1) reserves play a critical role for cyanobacteria to thrive under the often oligotrophic conditions in which they live, and (2) over-shading has a considerable effect as co-limiting factor on the growth of cyanobacteria. We argue that an individual DEB-based model in which multiple nutrient limitations are presented can be used to successfully describe cyanobacterium growth patterns in batch cultures.

It has been suggested that the relationship between income and the associated environmental pressure in terms of derived materials inputs and pollution levels may take an inverted-U shape, indicating a 'delinking' of environmental pressure from economic growth in relation to rising per capita incomes. The likelihood of such a relationship being persistent is discussed in the context of a simple macro model of industrial metabolism, and the possibility of 'relinking' clearly emerges. Data on specific indicators of environmental pressure (i.e., the throughput of materials, energy and the volume of transport) in 19 countries have been used to investigate patterns of delinking. The results suggest that delinking may not be persistent; already some advanced economies may be entering a new period of relinking. The relationships between environmental pressure and welfare in the medium long term may be N-shaped rather than inverted-U-shaped.

Policymakers at global level recognise that household biomass use in developing countries has significant health consequences. However, it is unclear how local-level health professionals perceive and respond to such health effects. This paper which is derived from the findings of a larger study on perceptions and responses to the harmful health effects of carrying heavy firewood loads and to smoke from cooking fires is based on a study conducted in South Africa among managers of health programmes and community nurses of Qaukeni and Mhlontlo municipalities in rural Eastern Cape. Interviews and participant observations were conducted in 2009 using ethnographic grounded theory approaches. In addition to a 10-month period of ethnographic fieldwork, ten programme managers and nurses in two villages were interviewed about health patterns in the villages that they serve, their perceptions of, and responses to the health effects of carrying heavy firewood loads, and inhalation of smoke from wood and dung cooking fires, their professional qualifications and experience, their own household energy use; and observations made as they served clinic clients. Results show that these programme managers and nurses perceive the health effects of carrying heavy loads of firewood and of cooking smoke as minor. Sometimes, nurses give women symptomatic relief for musculoskeletal pain resulting from carrying heavy loads. We posit that their perceptions are derived from customary neglect of work-related health and non-communicable diseases, cultural interpretations of womanhood, limited access to relevant information, and limited interactions between health and energy sector professionals. We conclude that culturally and gender-sensitive awareness programmes are needed for local-level health professionals to effectively address health effects of biomass collection and use. This paper provides new insights into overlooked differences between globally-driven initiatives to address health effects of biomass use and local perceptions.

The recommended power quality (PQ) indices in electric power systems are defined based on the discrete Fourier transform (DFT). DFT is mostly evaluated applying fast Fourier transform (FFT) algorithm which requires signals to be periodic in nature. Hence, it evaluates PQ indices accurately for stationary PQ disturbances only. However, in case of nonstationary PQ disturbances signal is aperiodic and FFT results in erroneous assessment due to spectral leakage phenomena. Furthermore, FFT cannot provide time information of the PQ indices as computation is performed in frequency domain only. Which is significant shortcoming of the FFT when dealing with time-varying PQ disturbances to extract dynamic signature of the signal. Thereby, this paper presents a framework of redefining PQ indices for stationary and nonstationary PQ disturbances employing time-frequency distribution (TFD) method. Among all TFDs, reduced interference distribution (RID) represents the most suitable properties for analyzing time-varying PQ disturbances. Hence, in this work, it is employed to reformulate PQ indices typically used in electric power systems. The results of two synthetic examples considering stationary and nonstationary PQ disturbances imply that the RID-based redefined PQ indices are closer to the actual values. Also, they provide more accurate results than the existing transient PQ indices and traditional FFT-based method.

Abstract Plant competitive interactions influence the effect of herbicides, and the effect of competitive interactions on plant responses may be important to include in the ecological risk assessment of herbicides. In the present study the effect of competitive interactions and sublethal doses of 2 herbicides on plant species was investigated in competition experiments and fitted to empirical competition models. Two nontarget species commonly found in agroecosystems (Centaurea cyanus L. and Silene noctiflora L.) and 2 herbicides (glyphosate and metsulfuron methyl) were used in separate experiments. Plants were sprayed at the 6- to 8-leaf stage. Effects of herbicide treatments and plant density were modeled by generalization of a discrete hyperbolic competition model. The 10% effective dose (ED10) was calculated for C. cyanus. All experiments showed that as density increased, plants were negatively affected. Furthermore, in all cases, C. cyanus remained a better competitor than S. noctiflora. Nevertheless, the density of S. noctiflora (competitor) was an influential element in determining the ED10 of C. cyanus measured at the mature stage. With herbicide exposure, the competitive interactions were further altered; C. cyanus was less affected by glyphosate when S. noctiflora increased to high density. In contrast, at the young stage, conspecific density was important in determining the sensitivity of C. cyanus to metsulfuron methyl, whereas the density of the competitor S. noctiflora had a limited influence. Overall, the results demonstrate the importance of integrating the effect of herbicide and species interactions measured at the reproductive stage into the ecological risk assessments of pesticides. Environ Toxicol Chem 2019;38:2053–2064. © 2019 SETAC.

Electric vehicles (EVs) are considered a substitute for fossil-fueled vehicles due to rising fossil fuel prices and accompanying environmental concerns, and their use is predicted to increase dramatically shortly. However, the widespread use of EVs and their large-scale integration into the energy system will present several operational and technological hurdles. In the energy industry, an innovative solution known as the EVs smart parking lot (SPL) is introduced to handle EV charging and discharging electricity and energy supply challenges. This paper investigates social equity access and mobile charging stations (MCSs) for EVs, where the owner of MCSs is the EV parking lot. Accordingly, a new self-scheduling model for SPLs is presented in this paper that incorporates scheduling of the MCSs as temporary charging infrastructures while considering social equity access and optimizes SPL energy generation and storage schedule. The main objectives of this research are to (i) develop MCSs accessibility measures and quantify the equity impacts of MCSs locations by modeling prioritized demand based on several indices; (ii) determine the optimal set-points of SPL components (i.e., combined heat and power (CHP), photovoltaic system, electrical and heat-energy storage, and MCSs) to manage electrical peak demand and to maximize the economic benefits of SPLs. Results indicate that the proposed demand prioritization function model can meet the required EV charging demands for prioritized events, and the self-scheduling model for SPLs satisfies the charging demand of the EVs in the SPL location. Also, the social equity access to the EV charging stations is satisfied by analyzing the operation of MCSs around the prioritized demand of the prioritized events and social equity access indices.

Changes in weather patterns pose a threat to the serviceability and long-term performance of roads, and porous asphalt (PA) roads are particularly sensitive to the freezing-thawing (FT) phenomenon. The main objective of this research is to assess the impact of climate change, particularly freezing and thawing cycles, on PA. Climate models predict changes in air temperature, not pavement temperature. To predict the climate change impact on pavements performance, this requires first establishing a relationship between air and road temperature and a correlation between pavement performance and FT cycles. This project focuses on the Netherlands, where PA pavement use has become mandatory, and recent severe winters have increased the discussion about the cold weather performance of porous asphalt and the potential challenges of changing winter weather patterns. When considering long-term changes in climate, the cost impacts of freeze-thaw on PA pavement are predicted to vary regionally and in most areas reach a point in the middle of the century when a reactive wait-and-see approach is more advantageous than proactive adaptation. Further research is suggested to refine the relationship between observed damage and freeze-thaw impacts on PA pavement.